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Abstract This paper focuses on layout modeling and optimization for a space control system. Majority of recent research works consider design components as constant elements over time. A new approach based on variable mass components is proposed in this paper for which the objective function is to minimize mass center variation (MCV) range over time. The proposed approach consists of Human-computer interaction (HCI) and Optimization methods to perform the layout. In the modeling phase, using defined inputs, all system components are determined. In the next step, mathematical model of achieved layout is defined. Mathematical model includes objective function, constraints, variables and parameters, play an important role in choosing appropriate optimization method. Based on mathematical model and design space, a gradient optimization method is selected. By applying this algorithm, optimum layout is proposed. Results of optimization and HCI design are compared. Comparison of the results shows that the optimization technique can significantly improve the results of the layout problem. At last, the results have analyzed and validated with similar research works. The results comparison show more efficiency and accuracy for the proposed method.

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In the current study, the streamline simulation technique is used for definition of a new objective function to optimize the production rates during water injection process. The streamline simulation technique, in comparison with common numerical methods for simulation of multi-phase flow in porous media, is much faster with less computational memory requirement. This method represents the key parameter of “Time of Flight” which helps to consider complex heterogeneity of porous media in a more easy way. In order to optimization of oil production rates from reservoir, a function based on averaged time of flight has been introduced which minimization of this function can be used to have uniform fronts of water for flooding of oil. For this target, two optimization techniques; the Artificial Bee Colony (ABC) and the Sequential Quadratic Programming (SQP) method are employed to optimize the objective function and their results are compared with each other. Advantages and disadvantages of these two methods are investigated and based on their advantages, a new hybrid approach is proposed which utilizes the benefits of both techniques to converge to the optimum solution. In the hybrid approach the SQP algorithm is initialized with the ABC method. In order to validate the mathematical model, a 2D homogeneous model used for optimization. Next a 2D heterogeneous model and a 3D complex reservoir model are investigated. In all the mentioned problems, it is observed that the hybrid approach, in comparision with the two other methods, can approach the optimum point with better accuracy and speed.